Cationic liposomes produced via ethanol injection method for dendritic cell therapy.

Cationic liposomes can be designed and developed in order to be an efficient gene delivery system for mammalian cells. Dendritic cell (DC) vaccines can be used to treat cancer, as cationic liposomes can deliver tumor antigens to cells while cells remain active. However, most methods used for liposome production are not able to reproduce in large scale the physicochemical and biological properties of liposomes produced in laboratory scale. In this context, ethanol injection method achieved promising results, although requiring post-treatment for size reduction and/or to remove residual ethanol. Thus, the purpose of this study was to generate cationic liposomes suitable for gene therapies via ethanol injection method in only one step (VEI) and compared to those submitted to a size reduction processes by microfluidization (MFV). For this, the method to produce cationic liposomes composed of egg phosphatidylcholine (EPC), 1,2-dioleoyl-3-trimethylammonium propane (DOTAP) and 1,2-dioleoylphosphatidylethanolamine (DOPE) was optimized using a statistical design approach. As a result, the size of VEI decreased from 290 nm to 110 nm and the polydispersity from 0.54 to 0.17. In the case of MFV, size decreased from 128 nm to 107 nm and polydispersity from 0.40 to 0.18. ST and MFV before and after optimization were also characterized in terms of morphology by transmission electron microscopy (TEM) and structure by differential scanning calorimetry (DSC). Finally, to show their potential in gene/immune therapies applications, DCs were stimulated by such liposomes. Cells internalized liposomes, increasing expression of the costimulatory molecule CD86 and inducing T lymphocyte proliferation.

Dendritic-tumor cell hybrids induce tumor-specific immune responses more effectively than the simple mixture of dendritic and tumor cells.

BACKGROUND AIMS: Dendritic cell (DC)-tumor cell hybrids have been used clinically in cancer immunotherapy, but their advantage over the simple mixture of tumor cells and DCs is still a matter of controversy. In this study, we compared DC-tumor cell hybrids with the non-fused mixture of DC and tumor cells directly in their ability to induce a specific immune response. METHODS: Hybrids were obtained by electrofusion of tumor cells and monocyte-derived DCs. Cell phenotype was evaluated by flow cytometry and antigen-presenting ability by co-culture with syngeneic T cells followed by tetramer analysis and interferon (IFN)-γ ELISPOT. RESULTS: Less than half the cells in the mixture expressed DC co-stimulatory molecules. Furthermore, DCs in the mixture had significantly lower expression of MHC class I molecules than DCs in the fusion. Conversely, nearly all CD11c(+)Her2/neu(+) hybrids expressed CD80, CD86, CD83, HLA-DR and MHC class I from both tumor cells and DCs. Using tumor cells constitutively expressing a cytomegalovirus (CMV) antigen, we show that expansion of CMV-specific cytotoxic T lymphocytes (CTLs) restricted by DCs' MHC class I molecules was higher when DC-tumor hybrids were the stimulators. Furthermore, only hybrids stimulated CTLs to produce IFN-γ in response to CMV-positive target cells. CONCLUSIONS: These data show the superiority of DC-tumor cell hybrids over their simple mixture as T-cell stimulators. Hybrids expressed more co-stimulatory and MHC molecules, induced higher antigen-specific T-cell expansion and were the only cells able to induce IFN-γ-producing antigen-specific T cells. Thus, these data offer further support for cancer immunotherapeutic approaches using DC-tumor cell hybrids.

Dendritic Cells Stimulated by Cationic Liposomes.

Immunotherapy of cancer aims to harness the immune system to detect and destroy cancer cells. To induce an immune response against cancer, activated dendritic cells (DCs) must present tumor antigens to T lymphocytes of patients. However, cancer patients' DCs are frequently defective, therefore, they are prone to induce rather tolerance than immune responses. In this context, loading tumor antigens into DCs and, at the same time, activating these cells, is a tempting goal within the field. Thus, we investigated the effects of cationic liposomes on the DCs differentiation/maturation, evaluating their surface phenotype and ability to stimulate T lymphocytes proliferation in vitro. The cationic liposomes composed by egg phosphatidylcholine, 1,2-dioleoyl-3-trimethylammonium propane and 1,2-dioleoylphosphatidylethanolamine (50/25/25% molar) were prepared by the thin film method followed by extrusion (65 nm, polydispersity of 0.13) and by the dehydration-rehydration method (95% of the population 107 nm, polydispersity of 0.52). The phenotypic analysis of dendritic cells and the analysis of T lymphocyte proliferation were performed by flow cytometry and showed that both cationic liposomes were incorporated and activated dendritic cells. Extruded liposomes were better incorporated and induced higher CD86 expression for dendritic cells than dehydrated-rehydrated vesicles. Furthermore, dendritic cells which internalized extruded liposomes also provided stronger T lymphocyte stimulation. Thus, cationic liposomes with a smaller size and polydispersity seem to be better incorporated by dendritic cells. Hence, these cationic liposomes could be used as a potential tool in further cancer immunotherapy strategies and contribute to new strategies in immunotherapy.

A robust deep learning workflow to predict CD8 + T-cell epitopes.

BACKGROUND: T-cells play a crucial role in the adaptive immune system by triggering responses against cancer cells and pathogens, while maintaining tolerance against self-antigens, which has sparked interest in the development of various T-cell-focused immunotherapies. However, the identification of antigens recognised by T-cells is low-throughput and laborious. To overcome some of these limitations, computational methods for predicting CD8 + T-cell epitopes have emerged. Despite recent developments, most immunogenicity algorithms struggle to learn features of peptide immunogenicity from small datasets, suffer from HLA bias and are unable to reliably predict pathology-specific CD8 + T-cell epitopes. METHODS: We developed TRAP (T-cell recognition potential of HLA-I presented peptides), a robust deep learning workflow for predicting CD8 + T-cell epitopes from MHC-I presented pathogenic and self-peptides. TRAP uses transfer learning, deep learning architecture and MHC binding information to make context-specific predictions of CD8 + T-cell epitopes. TRAP also detects low-confidence predictions for peptides that differ significantly from those in the training datasets to abstain from making incorrect predictions. To estimate the immunogenicity of pathogenic peptides with low-confidence predictions, we further developed a novel metric, RSAT (relative similarity to autoantigens and tumour-associated antigens), as a complementary to 'dissimilarity to self' from cancer studies. RESULTS: TRAP was used to identify epitopes from glioblastoma patients as well as SARS-CoV-2 peptides, and it outperformed other algorithms in both cancer and pathogenic settings. TRAP was especially effective at extracting immunogenicity-associated properties from restricted data of emerging pathogens and translating them onto related species, as well as minimising the loss of likely epitopes in imbalanced datasets. We also demonstrated that the novel metric termed RSAT was able to estimate immunogenic of pathogenic peptides of various lengths and species. TRAP implementation is available at: https://github.com/ChloeHJ/TRAP . CONCLUSIONS: This study presents a novel computational workflow for accurately predicting CD8 + T-cell epitopes to foster a better understanding of antigen-specific T-cell response and the development of effective clinical therapeutics.

Potential CD8+ T Cell Cross-Reactivity Against SARS-CoV-2 Conferred by Other Coronavirus Strains.

While individuals infected with coronavirus disease 2019 (COVID-19) manifested a broad range in susceptibility and severity to the disease, the pre-existing immune memory to related pathogens cross-reactive against SARS-CoV-2 can influence the disease outcome in COVID-19. Here, we investigated the potential extent of T cell cross-reactivity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that can be conferred by other coronaviruses and influenza virus, and generated an in silico map of public and private CD8+ T cell epitopes between coronaviruses. We observed 794 predicted SARS-CoV-2 epitopes of which 52% were private and 48% were public. Ninety-nine percent of the public epitopes were shared with SARS-CoV and 5.4% were shared with either one of four common coronaviruses, 229E, HKU1, NL63, and OC43. Moreover, to assess the potential risk of self-reactivity and/or diminished T cell response for peptides identical or highly similar to the host, we identified predicted epitopes with high sequence similarity with human proteome. Lastly, we compared predicted epitopes from coronaviruses with epitopes from influenza virus deposited in IEDB, and found only a small number of peptides with limited potential for cross-reactivity between the two virus families. We believe our comprehensive in silico profile of private and public epitopes across coronaviruses would facilitate design of vaccines, and provide insights into the presence of pre-existing coronavirus-specific memory CD8+ T cells that may influence immune responses against SARS-CoV-2.

Frequency determination of breast tumor-reactive CD4 and CD8 T cells in humans: unveiling the antitumor immune response.

As cancer immunotherapy gains importance, the determination of a patient's ability to react to his/her tumor is unquestionably relevant. Though the presence of T cells that recognize specific tumor antigens is well established, the total frequency of tumor-reactive T cells in humans is difficult to assess, especially due to the lack of broad analysis techniques. Here, we describe a strategy that allows this determination, in both CD4 and CD8 compartments, using T cell proliferation induced by tumor cell-lysate pulsed dendritic cells as the readout. All 12 healthy donor tested had circulating CD4 and CD8 tumor cell-reactive T cells. The detection of these T cells, not only in the naïve but also in the memory compartment, can be seen as an evidence of tumor immunosurveillance in humans. As expected, breast cancer patients had higher frequencies of blood tumor-reactive T cells, but with differences among breast cancer subtypes. Interestingly, the frequency of blood tumor-reactive T cells in patients did not correlate to the frequency of infiltrating tumor-reactive T cells, highlighting the danger of implying a local tumor response from blood obtained data. In conclusion, these data add T cell evidence to immunosurveillance in humans, confirm that immune parameters in blood may be misleading and describe a tool to follow the tumor-specific immune response in patients and, thus, to design better immunotherapeutic approaches.

Tolerogenic IDO(+) Dendritic Cells Are Induced by PD-1-Expressing Mast Cells.

Mast cells (MCs) are tissue resident cells, rich in inflammatory mediators, involved in allergic reactions, and with an increasingly recognized role in immunomodulation. Dendritic cells (DCs), on the other hand, are central to the determination of immune response patterns, being highly efficient antigen-presenting cells that respond promptly to changes in their microenvironment. Here, we show that direct cell contact between immature monocyte-derived DCs (iDCs) and MC bends DCs toward tolerance induction. DCs that had direct contact with MC (MC-iDC) decreased HLA-DR but increased PD-L1 expression and stimulated regulatory T lymphocytes, which expresses FoxP3(+), secrete TGF-ß and IL-10, and suppress the proliferation of mitogen-stimulated naïve T lymphocytes. Furthermore, MC-iDC expressed higher levels of indoleamine-2,3-deoxigenase (IDO), a phenomenon that was blocked by treatment of MC with anti-PD-1 or by the treatment of DCs with anti-PD-L1 or anti-PD-L2, but not by blocking of H1 and H2 histamine receptors on DCs. Contact with MC also increased phosphorylated STAT-3 levels in iDCs. When a STAT-3 inhibitor, JSI-124, was added to the DCs before contact with MC, the MC-iDC recovered their ability to induce allogeneic T cell proliferation and did not increase their IDO expression.

Dendritic cell membrane CD83 enhances immune responses by boosting intracellular calcium release in T lymphocytes.

CD83 is a marker of mDCs directly related to their lymphostimulatory ability. Some data suggest that it has a central role in the immune system regulation, but how this function is performed remains to be determined. This work aimed to analyze the influence of CD83, present in mDCs, in the modulation of calcium signaling in T lymphocytes. Mo were differentiated into iDCs and activated with TNF-α. iDCs were treated, 4 h before activation, with siRNACD83, to reduce CD83 expression. Purified allogeneic T lymphocytes were labeled with the calcium indicator Fluo-4-AM, and calcium mobilization in the presence of mDCs was analyzed. CD83 knockdown mDCs induced lower calcium signal amplitude in T lymphocytes (29.0±10.0) compared with siRNAscr-treated mDCs (45.5±5.3). In another set of experiments, surface mDC CD83 was blocked with a specific mAb, and again, decreased calcium signaling in T lymphocytes was detected by flow cytometry and microscopy (fluorescence and confocal). In the presence of antibody, the percentage of responding T cells was reduced from 58.14% to 34.29%. As expected, anti-CD83 antibodies also reduced the proliferation of T lymphocytes (as assessed by CFSE dilution). Finally, in the absence of extracellular calcium, CD83 antibodies abrogated T cell signaling induced by allogeneic mDCs, suggesting that the presence of CD83 in mDC membranes enhances T lymphocyte proliferation by boosting calcium release from intracellular stores in these cells.